Semiconductor devices such as logic and memory devices are typically fabricated by a sequence of processing steps applied to a specimen. The various features and multiple structural levels of the semiconductor devices are formed by these processing steps. For example, lithography among others is one semiconductor fabrication process that involves generating a pattern on a semiconductor wafer. Additional examples of semiconductor fabrication processes include, but are not limited to, chemical-mechanical polishing, etch, deposition, and ion implantation. Multiple semiconductor devices may be fabricated on a single semiconductor wafer and then separated into individual semiconductor devices.
Multiple patterning techniques are commonly employed to increase the resolution of features printed onto the semiconductor wafer for a given lithographic system. Metrology processes are used at various steps during a semiconductor manufacturing process to detect defects on wafers to promote higher yield, including wafers manufactured using multiple patterning techniques.
Optical metrology techniques offer the potential for high throughput measurement without the risk of sample destruction. A number of optical metrology based techniques including scatterometry and reflectometry implementations and associated analysis algorithms are commonly used to characterize critical dimensions, film thicknesses, composition and other parameters of nanoscale structures.
In general, the number of parameters that need to be measured increases as the geometric complexity of the metrology target increases. This increases the risk of correlation among parameters under measurement that limits measurement performance.
In addition, optical metrology suffers low sensitivity to some parameters of metrology targets, particularly multiple patterned targets. Typically, optical metrology techniques employing physical, model based measurements require a parameterized, geometric model of the patterned structure. Example parameters include critical dimension, pitch walk, or other parameters of interest. In addition, an accurate electromagnetic model of the interaction between the optical system and the structure under measurement is required to simulate signals generated during measurement. Nonlinear regression of simulated signals against measured signals is applied to determine parameters of the modeled structure. This approach requires accurate modeling of the structure and the material properties.
Often, the measurement process suffers from weak sensitivity to critical parameters, and in some cases physical model based measurement techniques result in low sensitivity and poor precision. The lack of sensitivity of measured optical signals to these critical parameters makes it extremely difficult to monitor and control the patterning process.
In some examples, an optical metrology system is employed to measure a target. Typically, several parameters are measured, such as critical dimension (CD), ΔCD, average CD, sidewall angle (SWA), and other shape parameters. Exemplary systems are described in U.S. Patent Publication No. 2015/0176985, assigned to KLA-Tencor Corporation, the contents of which are incorporated herein by reference in their entirety.
In some examples, process information associated with a wafer under measurement is communicated to an optical metrology tool to enhance the optical measurement. In one example, lithography dosage at two different patterning steps of a litho-etch-litho-etch (LELE) multiple patterning process are communicated to an optical metrology tool. If the first lithography dosage is larger than the second dosage in the LELE process, then it is known that one critical dimension parameter (CD1) will be smaller than another critical dimension parameter (CD2). By enforcing this constraint, degeneracy in the optical metrology measurement model is broken, enabling more accurate measurement results. Although process information has been shown to improve measurement results in some specific examples, there are other examples where process information is either not available or not helpful.
In some other examples, a measurement system includes two metrology techniques. Such systems are commonly referred to as “hybrid” metrology systems. Exemplary systems are described in U.S. Patent Publication No. 2017/0018069, by Alok Vaid et al., the contents of which are incorporated herein by reference in their entirety. However, measurement results obtained from prior art hybrid metrology systems typically involve determining a value of a parameter of interests based on a weighted average of measurement results from two different measurement techniques.
Metrology applications involving the measurement of patterned structures present challenges due to increasingly small resolution requirements, multi-parameter correlation, increasingly complex geometric structures, and increasing use of opaque materials. Thus, methods and systems for improved measurements are desired.